Learning cortical representations through perturbed and adversarial dreaming. (arXiv:2109.04261v2 [q-bio.NC] UPDATED)

Humans and other animals learn to extract general concepts from sensory
experience without extensive teaching. This ability is thought to be
facilitated by offline states like sleep where previous experiences are
systemically replayed. However, the characteristic creative nature of dreams
suggests that learning semantic representations may go beyond merely replaying
previous experiences. We support this hypothesis by implementing a cortical
architecture inspired by generative adversarial networks (GANs). Learning in
our model is organized across three different global brain states mimicking …

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